Mass casualty event scenarios and political shifts
2020 Election outcomes and the U.S. Covid-19 pandemic
Bibliographic Data
| ID | 12450306 |
|---|---|
| Authors | Andrew F Johnson (0000-0001-9424-9605, Texas A&M University – Corpus Christi, corresponding author), Wendi Pollock (0000-0002-9043-8588, Department of Social Sciences, Texas A&M University-Corpus Christi, Corpus Christi, Texas, USA), Beth Rauhaus (0000-0001-6910-288X, Department of Social Sciences, Texas A&M University-Corpus Christi, Corpus Christi, Texas, USA) |
| Year | 2020 |
| Volume | 42 |
| Issue | 2 |
| Pages | 249-264 |
| Publication date | 2020-04-02 |
| Peer Reviewed | Yes |
| Open Access | No |
| Type | ARTICLE |
| Venue | Administrative Theory & Praxis (JOURNAL) |
| Journal identifiers | ISSN: 1084-1806 • E-ISSN: 1949-0461 |
| Publisher | Taylor & Francis (PUBLISHER • GB) |
| DOI | 10.1080/10841806.2020.1752978 |
| OpenAlex | W3017142226 |
| Language | EN |
| Citations received | 10 |
| References cited | 9 |
COVID-19 models indicate a mass casualty event may potentially occur in the United States. Among numerous social and economic changes, the potential to reshape the political landscape exists. The theoretical perspective of politics-administration dichotomy is used to examine the rhetoric, power, and authority of public health messages during the pandemic. This study considers political shifts using state-level data on population, historical voter turnout, and projected COVID-19 cases number coupled with national-level data on voter participation by age group and COVID-19 fatality rates. Developing a formula to calculate these data, we project the extent to which the number of voters from each party could diminish. The analysis shows the potential for significant political changes due to the disproportionate loss of older voters in key swing states in the months leading to the 2020 presidential election
Coronavirus disease 2019 (COVID-19 · Pandemic · Political economy · Political science · Politics · Population · Presidential election · Presidential system · Sociology · State (computer science · Turnout · Voter registration · Voting · COVID-19 epidemiological studies · COVID-19 Pandemic Impacts · Demography · Disaster Management and Resilience · Law · Medicine · Public Administration
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| Unique citing works | 10 |
|---|---|
| Citations per year | 1,67 |
| Citation span | 2020 - 2026 (7) |
| Citation velocity | current |
| Highly cited | No |
| Citation types | Neutral: 10 |